On Thu, Jun 18, 2015 at 12:15 PM, Jason Sarich <[email protected]> wrote:
> Hi Justin, > > I can't tell for sure why this is happening, have you tried using quad > precision to make sure that numerical cutoffs isn't the problem? > > 1 The Hessian being approximate and the resulting implicit computation is > the source of the cutoff, but would not be causing different convergence > rates in infinite precision. > > 2 the local size may affect load balancing but not the resulting > norms/convergence rate. > This sounds to be like the preconditioner is dependent on the partition. Can you send -tao_view -snes_view Matt > Jason > > > On Thu, Jun 18, 2015 at 10:44 AM, Justin Chang <[email protected]> > wrote: > >> I solved a transient diffusion across multiple cores using TAO BLMVM. >> When I simulate the same problem but on different numbers of processing >> cores, the number of solve iterations change quite drastically. The >> numerical solution is the same, but these changes are quite vast. I >> attached a PDF showing a comparison between KSP and TAO. KSP remains >> largely invariant with number of processors but TAO (with bounded >> constraints) fluctuates. >> >> My question is, why is this happening? I understand that accumulation of >> numerical round-offs may attribute to this, but the differences seem quite >> vast to me. My initial thought was that >> >> 1) the Hessian is only projected and not explicitly computed, which may >> have something to do with the rate of convergence >> >> 2) local problem size. Certain regions of my domain have different number >> of "violations" which need to be corrected by the bounded constraints so >> the rate of convergence depends on how these regions are partitioned? >> >> Any thoughts? >> >> Thanks, >> Justin >> > > -- What most experimenters take for granted before they begin their experiments is infinitely more interesting than any results to which their experiments lead. -- Norbert Wiener
